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Phase Repeatable Synthesizers as a New Harmonic Phase Standard for Nonlinear Network Analysis
(2018)
Die Erfindung betrifft ein Bussystem enthaltend Busleitungen, an denen eine Anzahl von Busteilnehmern über einen Transceiver anschließbar sind, wobei der Transceiver eine bidirektionale Kommunikation zwischen mindestens zwei Busteilnehmern bewirkt, wobei auf einer busabgewandten Seite des Transceivers sich an denselben eine Zwischenbrückeneinheit anschließt, die mindestens zwei Sender-/Empfänger-Paare enthaltend jeweils einen Sender und einen Empfänger aufweist, wobei der Sender einen Senderoszillator, eine Amplituden- und/oder Phasen- und/oder Frequenzmodulator sowie eine Antenne aufweist und wobei der Empfänger einen Mischer aufweisenden Demodulator sowie eine Antenne aufweist, wobei ein erstes Sender-/Empfänger-Paar über eine Funkschnittstelle mit dem zweiten Sender-/Empfänger-Paar miteinander gekoppelt sind.
Wireless CAN
(2018)
Das vorgestellte System zu Wireless CAN bietet die Möglichkeit, CAN kabellos zu übertragen. Beide vorgestellten und entwickelten Konzepte funktionieren korrekt und ermöglichen den Auf-bau von kabellosen CAN Schnittstellen. Durch den kleinen Aufbau kann diese Technologie auch für eingebettete Systeme verwendet werden. Zudem bietet dieser Ansatz die Möglichkeit, durch die Entwicklung von geeigneten ICs die Größe des Systems bis auf Bauteilgröße zu reduzieren, um eine noch bessere Integration in eingebettete Systeme zu ermöglichen. Dadurch wird die Technologie attraktiv für Einsatzgebiete, wo die oben aufgelisteten Vorteile zum Tragen kommen können. Diese Einsatzgebiete können sowohl im Automobil als auch im Industriebereich liegen.
In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics.
During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results.
In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.
In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog’s forward-search DT planning algorithm, these formulas are evaluated in order to find the agent’s optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
20 Years of RoboCup
(2016)